COMM1190 Data, Insights and Decisions
Assessment 1: Initial report
TelcomCo churn rate project
The General Manager (GM) at TelcomCo is mandated to deliver a customer retention update to
the Board of Directors. To prepare, the GM initiated a pilot study led by a junior analyst using
sample data on customer service usage patterns.
The junior analyst’s initial findings, documented in a memo (Appendix A), were based on pilot
data from July 2024. As a Business Analyst at TelcomCo, you have been asked to conduct a deeper
analysis using an expanded dataset to investigate churn rate factors and offer actionable
recommendations for improving customer retention. Additionally, the GM raised concerns about
the memo’s quality, requiring a revised report.
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Appendix A: Analysis of customer pilot data
MEMORANDUM
DATE: 12 September 2024
TO: Board of Directors
RE: Marketing Analytics Report
Introduction
This report presents an initial statistical analysis of customer data from the company’s central
database. The dataset includes information on customer demographics, account types, service
usage, churn rate rates, and spending patterns. The analysis focuses on pilot data from July 2024
and is structured into four sections: customer demographics, monthly charges, customer
satisfaction, and recommendations.
Customer Characteristics
Figure 1 and Table 1 summarise key customer characteristics from the pilot sample, including
demographic information and service usage insights.
Figure 1: Customer Characteristics
The gender distribution among customers is evenly split. The average age of the customers is
46.64 years, with an average tenure of 32.25 months. Approximately 75% of customers do not
have dependents, and over 60% are not living with a partner.
Figure 2: Age
Gender
Male Female
Partner
Yes No
Dependents
Yes No
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According to Figure 2, the customer age distribution peaks in the 19-25 age group, with about
15% of customers being senior citizens. The distribution is not symmetrical, indicating a
concentration in younger age groups.
Table 1: Customer Characteristics
Statistic Tenure Age
Mean 32.25 46.64
Median 29 46
Mode 1 21
Standard Deviation 24.84 19.20
Skewness 0.26 0.38
Range 72 71
Minimum 0 19
Maximum 72 90
After analysing customer characteristics, we explore the financial impact through
transaction sales data.
Transaction sales
The monthly charges represent the transaction sales, indicating the amount customers pay for
the company’s telecommunications services. Table 2 shows summary statistics for these charges.
Based on a sample of 999 customers, the average spending is $66.48, while the median is $74.25,
suggesting a negatively skewed distribution. A mode of $19.90 indicates a significant portion of
customers pay low charges, possibly reflecting a large group of customers subscribing to lower-
tier service packages.
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Table 2: Transaction Sales
Statistic Monthly Charges
Mean 66.48
Standard Error 0.95
Median 74.25
Mode 19.90
Standard Deviation 29.93
Sample Variance 896.07
Kurtosis -1.20
Skewness -0.30
Range 97.30
Minimum 18.95
Maximum 116.25
Sum 66,413.50
Count 999
A correlation analysis was conducted, and the results are shown in Table 3. There is a moderate
positive correlation between tenure and monthly charges, indicating that customers who stay
longer tend to spend more. However, tenure has a weak negative correlation with age,
suggesting that age and tenure are not closely related.
Table 3: Correlation Matrix
Variable Age Monthly Charges Tenure
Age 1 0.176 -0.028
Monthly Charges 0.176 1 0.252
Tenure -0.028 0.252 1
Customer churn rate
The overall churn rate is 25%, as depicted in Figure 3. Figure 4 shows that female customers are
slightly more likely to churn rate than male customers. Additionally, Figure 5 reveals that
customers not living with a partner are more prone to churn rate, as illustrated by the percent
stacked bar chart.
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Figure 3: Churn rate
Figure 4: Churn rate by Gender
Figure 5: Churn rate by Living Status
Churn
Yes No
0
50
100
150
200
250
300
350
400
450
Yes No
Churn rate by Gender
Female Male
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Yes No
Churn rate by Living Status
Partner-Yes Partner-No
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Conclusion
• A high proportion of customers are in the youngest age bracket, contributing to the lower
mean spending than the median.
• Female customers and those not living with a partner show a higher propensity to churn
rate.
• A positive correlation exists between tenure and monthly spending, indicating that
customers who stay longer tend to spend more. TelcomCo can leverage this information
to reduce churn rate (e.g., loyalty programs or incentives for long-term customers).
Recommendation
The small pilot dataset limits the reliability of these insights. More customer data should be
collected to generate a more robust analysis, and additional variables should be explored.
To enhance the reliability of the analysis, TelcomCo should expand the dataset by collecting
additional customer data, such as customer engagement metrics, service quality feedback, or
payment history. This would enable more comprehensive insights into churn behaviour.
Additionally, future analyses should explore new variables like customer satisfaction over time
and the impact of promotional offers. A more extensive analysis could involve segmenting
customers by service package or region to tailor retention strategies effectively.
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Appendix B: Data dictionary
Variable Description
CustomerID Unique identifier for each customer.
Gender Gender of the customer (Male, Female).
Age Age of the customer in years (18+).
Partner Whether the customer lives with a partner (Yes, No).
Dependents Whether the customer has dependents (Yes, No).
Tenure
Number of months the customer has stayed with the company. For analytical
purpose, the tenure can be classified into three broad categories: short-term (<9
months); medium term (between 9 and 18 months) and long-term (greater than
18 months)
InternetService Type of internet service (Fiber optic, 5G, DSL, No service).
OnlineProtect Level of online security/back-up (0: None, 1: Security, 2: Backup, 3: Both).
TechSupport Type of tech support (1: Chatbot, 2: Email, 3: Phone).
Streaming Streaming subscription status (0: None, 1: TV, 2: Movies, 3: Both).
Outage Frequency of service outages (Occasional, Frequent).
ContractType Type of contract (1: Month-to-month, 12: One year, 24: Two year).
MonthlyCharges Monthly amount charged to the customer.
MultipleLines
Whether the customer has subscribed to more than one phone line (0: no phone
line; 1: one phone line and 2: more than one line)
Churn Whether the customer churns (Yes, No).
Pilot Indicates whether data is from the pilot study (1: Yes, 0: No).